A novel business cycle surveillance system using the query logs of search engines
Knowledge-Based Systems
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Identifying status of business cycles is critical to governments and enterprises when building business strategies. Traditionally, economic variables, such as industrial production, stock price index, manufacturing sales, are selected to compose business cycle indicators, which altogether evaluate business cycle status. In general, the release of economic variables involves long data processes that delay the announcement of business status. The announced business status thus is not timely and could increase the uncertainty of business decision making. In this work, we employ query logs of search engines for business cycle identification. As query logs are readily available through online Web services, they can provide timely and accurate information about business status. We propose a feature selection method to identify query terms appropriate for business cycle identification. Evaluation results show that the identified query terms are effective indicators and the proposed method models business cycles correctly.